Showing papers by "John Wilson published in 1996"

Religion and marital dependency

Abstract: Les statistiques de la National survey of families and households sont utilisees afin de determiner l'impact de la religion sur la dependance matrimoniale. Les epoux qui appartiennent aux denominations attachant une plus grande valeur au mariage et a la stabilite matrimoniale doivent temoigner d'une plus grande dependance ainsi que ceux qui sont engages dans la vie de l'Eglise ou qui appartiennent a la meme denomination. L'affiliation religieuse augmente les chances de dependance matrimoniale. L'effet de l'homogamie est plus important chez les fondamentalistes

GIS-based solute transport modeling applications: scale effects of soil and climate data input

Abstract: The Weather Generator (WGEN) and Chemical Movement through Layered Soils (CMLS) computer models were modified and combined with two sets of soil and climate inputs to evaluate the impact of input data map resolution on model predictions. The basic soil and climate inputs required by WGEN and CMLS were acquired from either : (i) the USDA-NRCS State Soil Geographic Database (STATSGO) database ; (ii) the USDA-NRCS (County) Soil Survey Geographic (SSURGO) database ; (iii) the Montana Agricultural Potential System (MAPS) database (which divides Montana into approximately 18 000 twenty square kilometer cells and stores more than 200 different land and climate characteristics for each of these cells) ; and (iv) a series of fine-scale monthly climate surfaces developed by the authors (0.55 km 2 cell size) using thin-plate splines, published climate station records, and USGS Digital Elevation Models (DEMs). Fifteen years of daily precipitation and evapotranspiration (ET) values were generated and combined with soil and pesticide inputs in CMLS to estimate the depth of picloram 4-amino-3,5,6-trichloro-2-pyridinecarboxylic acid) movement at the end of the growing season for every unique combination (polygon) of soil and climate in a 320 km 2 area in Teton County, Montana. Results indicate that : (i) the mean depths of picloram movement predicted for the study area with the SSURGO (county) soils and MAPS (coarse-scale) climate information and the two model runs using the fine-scale climate data were significantly different from the values predicted with the STATSGO (state) soils and MAPS climate data (based on a new variable containing the differences between the depths of leaching predicted with the different input data by soil/climate map unit and testing whether the mean difference was significantly different from zero at the 0.01 significance level) ; and (ii) CMLS identified numerous (small) areas where the mean center of the picloram solute front was likely to leach beyond the root zone when the county soils information was used. This last measure may help to identify areas where potential chemical applications are likely to contaminate groundwaters.

Input parameter and model resolution effects on predictions of solute transport

Abstract: Model predictions of solute transport using larger scale soil and climatic data sets may be useful for classifying mapping units based on their susceptibility to chemical leaching. However, model predictions based on input data sets with low spatial resolution may not accurately reflect transport processes occurring in situ. The goal of the current study was to compare several modeling approaches that might be applicable for classifying soil mapping units (1 :24 000) according to their leaching potential to (i) model results based on detailed site-specific measurements and (ii) observed data collected at a field site (Borollic Calciorthid) in southwestern Montana. Data from a 2-yr field study of pentafluorobenzoic acid (PFBA), 2,6-difluorobenzoic acid (DFBA) and dicamba (3,6-dichloro-2-methoxybenzoic acid) transport in fallow and cropped systems under two water application levels were compared to simulations obtained using the Chemical Movement in Layered Soils (CMLS) and Leaching and Chemistry Estimation (LEACHM) models. The resolution of model input parameters was varied based on sources of data. In Case I, model inputs were obtained primarily from detailed soil profile characterization and site-specific measurements of precipitation, irrigation, and pan evaporation. LEACHM predictions were also generated using estimated conductivity and retentivity functions from textural data obtained from the USDA-NRCS Soil Survey (SSURGO) database (Cases 2 and 3). CMLS predictions were generated using (i) detailed site-specific measurements (Case 1) and (ii) estimated volumetric water contents from textural data (SSURGO) and estimated dally precipitation and evapotranspiration (ET) from the Weather Generator (WGEN) and Montana Agricultural Potentials (MAPS) climate database (Cases 2 and 3). Comparison of observed and simulated mean solute travel times showed that (i) LEACHM and CMLS performed adequately with high-resolution model inputs, (ii) model performance declined when field conditions were conducive to preferential flow, (iii) estimated K 5 values from regression equations based on textural data were problematic for generating adequate predictions using LEACHM, and (iv) CMLS predictions were less sensitive to data input resolution, due in part to the fact that CMLS provides an oversimplified description of transport processes.

A comparison of hand- and spline-drawn precipitation maps for mountainous Montana

Abstract: Average annual precipitation for the period 1961-1990 was estimated for a mountainous region in Montana with a Laplacian thin-plate spline (ANUSPLIN) and compared to a hand-drawn map. Input data included latitude, longitude, and elevation from a three-arc-second U.S. Geological Survey Digital Elevation Model of the Bozeman and Billings 1° x 2° topographic quadrangles and precipitation data at 96 stations. The two maps are similar in appearance. Digital comparison of the two maps with ARC/INFO's Grid tools shows that mean annual precipitation for the hand-contoured map is 22.9 inches and for the ANUSPLIN map is 23.7 inches. Of the 5,760,000 cells, 53 percent showed no difference between ANUSPLIN and hand-drawn maps ; 19 percent showed a two-inch difference, and 28 percent showed more than 2 inches difference. Input data and model output at the same location are not different (standard deviation 1.77, p-value 0.76). Hand-drawn maps show two inches more precipitation during the 1961-90 period than during the 1941-1970 period. Similarly, measured data at 73 sites for the period 1961-1990 are on average 2.4 inches higher than the same stations during the 1941-1970 period. The difference is significant (p-value < 0.0001).